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Looking Back at 2018 APM Predictions - Did They Come True? Part 2

Jonah Kowall
Spacelift

I would like to highlight some of the predictions made at the start of 2018, and how those have panned out, or not actually occurred. I will review some of the predictions and trends from APMdigest's 2018 APM Predictions. Here is Part 2: Start with Looking Back at 2018 APM Predictions - Did They Come True? Part 1

Microtrends

The use of chatbots and other connected assistants have not yielded any benefits in the IT Operations space in 2018, but there are many emerging startups in this area looking to change that over the coming years. While several companies such as ServiceNow and Microsoft made acquisitions in this market, they haven’t produced anything tangible, especially not in 2018. Time will tell if these are a passing fad or they become a cornerstone of computing. IoT is still nascent, especially in the APM market. The predictions about its growing importance and adoption of APM for IoT are still generally immature and early stage. There are some incredible stories for those doing this, but it’s still a very small number today. Those predictions around IoT are likely too early. Similarly, Blockchain doesn’t even go there, way too early considering how few real implementations of Blockchain are implemented in production at this point. Maybe in another five years, we can begin to make some predictions, but it will likely be longer before Blockchain performance management solutions are needed by the market.

Culture and Communication

The biggest barrier to transformation is culture and people. This has been clear from every major CIO survey conducted in the last 10 years of economic growth in this bull market. Our communications and the way we do incident response have evolved significantly. The players in this space are solving an extremely important problem, one which MAY change the culture of an organization. This trend will continue as these technologies become essential to better communication of increasingly distributed workforces. The codification of the role of the SRE by the excellent second book from Google has helped the industry understand how to apply DevOps in an even more concrete manner. The predictions about SRE were spot on, as SRE has become the gold standard for managing and operating applications. Still early for most organizations, but now on the radar. There were several predictions about SRE for the past year. I would, however, say that the vendors who predicted DevOps and culture change by a tool were sadly far from reality. Tools don’t change cultures, but cultural changes often require tool changes. Wrapping up a great 2018, I wish everyone a productive and creative 2019 where we can listen, learn, innovate, share, and advance our group of APM vendors and practitioners. There are many problems to solve, and new approaches being invented daily by this amazing community.

Jonah Kowall is SVP of Product and Design at Spacelift

Hot Topics

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...

Looking Back at 2018 APM Predictions - Did They Come True? Part 2

Jonah Kowall
Spacelift

I would like to highlight some of the predictions made at the start of 2018, and how those have panned out, or not actually occurred. I will review some of the predictions and trends from APMdigest's 2018 APM Predictions. Here is Part 2: Start with Looking Back at 2018 APM Predictions - Did They Come True? Part 1

Microtrends

The use of chatbots and other connected assistants have not yielded any benefits in the IT Operations space in 2018, but there are many emerging startups in this area looking to change that over the coming years. While several companies such as ServiceNow and Microsoft made acquisitions in this market, they haven’t produced anything tangible, especially not in 2018. Time will tell if these are a passing fad or they become a cornerstone of computing. IoT is still nascent, especially in the APM market. The predictions about its growing importance and adoption of APM for IoT are still generally immature and early stage. There are some incredible stories for those doing this, but it’s still a very small number today. Those predictions around IoT are likely too early. Similarly, Blockchain doesn’t even go there, way too early considering how few real implementations of Blockchain are implemented in production at this point. Maybe in another five years, we can begin to make some predictions, but it will likely be longer before Blockchain performance management solutions are needed by the market.

Culture and Communication

The biggest barrier to transformation is culture and people. This has been clear from every major CIO survey conducted in the last 10 years of economic growth in this bull market. Our communications and the way we do incident response have evolved significantly. The players in this space are solving an extremely important problem, one which MAY change the culture of an organization. This trend will continue as these technologies become essential to better communication of increasingly distributed workforces. The codification of the role of the SRE by the excellent second book from Google has helped the industry understand how to apply DevOps in an even more concrete manner. The predictions about SRE were spot on, as SRE has become the gold standard for managing and operating applications. Still early for most organizations, but now on the radar. There were several predictions about SRE for the past year. I would, however, say that the vendors who predicted DevOps and culture change by a tool were sadly far from reality. Tools don’t change cultures, but cultural changes often require tool changes. Wrapping up a great 2018, I wish everyone a productive and creative 2019 where we can listen, learn, innovate, share, and advance our group of APM vendors and practitioners. There are many problems to solve, and new approaches being invented daily by this amazing community.

Jonah Kowall is SVP of Product and Design at Spacelift

Hot Topics

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...